Model Calculations Research Articles

Non-relativistic torque and Edelstein effect in non-collinear magnets

The Edelstein effect is the origin of the spin-orbit torque: a current-induced torque that is used for the electrical control of ferromagnetic and antiferromagnetic materials. This effect originates from the relativistic spin-orbit coupling, which necessitates utilizing materials with heavy elements. Here, we show that in magnetic materials with non-collinear magnetic order, the Edelstein effect and, consequently, a current-induced torque can exist even in the absence of the spin-orbit coupling. Using group symmetry analysis, model calculations, and realistic simulations on selected compounds, we identify large classes of non-collinear magnet candidates and demonstrate that the current-driven torque is of similar magnitude as the celebrated spin-orbit torque in conventional transition metal structures. We also show that this torque can exist in an insulating material, which could allow for highly efficient electrical control of magnetic order.

SELECTION OF A MRP SYSTEM FOR OIL AND GAS DEPOSITS

A number of serious problems arise in the development of sub-gas zones of oil and gas deposits due to the joint occurrence of oil and gas. The key problem is gas breakthrough from the gas cap to oil wells. This entails an increase in the gas factor (GOR), a rapid and intense decrease in pressure in the gas cap. If there is a reservoir pressure maintenance system or an active aquifer as a result of a decrease in reservoir pressure in the gas cap, oil may be pushed back into it, which leads to a rise in gas-oil contact, jamming of mobile oil in the «dry sandstones» of the gas cap, which in turn leads to a decrease in reserves of mobile oil and a decrease in the oil recovery factor (ORF). All this together allows us to consider oil in the sub-gas zones as hard-to-recover reserves.Preventing and combating the negative consequences of gas breakthrough from the gas cap to oil wells is a complex task and consists of several areas, such as selection of rational drilling of production and injection wells, selection of optimal operating modes for them, use of inflow control devices or performance of repair and isolation work to limit inflow from intervals with gas breakthrough, periodic shutdown of wells to disband gas cones. The ultimate goal of solving these problems is to increase the oil recovery factor and economic efficiency indicators for the development of sub-gas zones.Due to the variety of ways to optimize the development of oil and gas reservoirs, it is not possible to cover them all in one work, therefore, the tasks associated with optimizing the reservoir pressure maintenance system are considered. It is worth noting that in comparison with the development of oil reservoirs, the presence of a gas cap significantly complicates this task due to the lack of analytical solutions for three-phase filtration. For this reason, the selection of the optimal parameters of the reservoir pressure maintenance system is usually carried out either by multivariate calculations in the hydrodynamic model (HDM), or by the method of analogies or the implementation of pilot tests of various approaches.In this study, an approach based on multivariate numerical calculations using the sector model of the development element of the gas zone was used. As a result of calculations, it was shown that when choosing the optimal parameters of the reservoir pressure maintenance system, it is advisable to use a differentiated approach, which consists in the fact that these parameters must be set individually for zones with different ratios of oil-saturated and gas-saturated thicknesses.

Ab initio study of Z(N) = 6 magicity

Abstract The existence of magic numbers of protons and neutrons in nuclei is essential for understanding nuclear structure and fundamental nuclear forces. Over decades, researchers have conducted theoretical and experimental studies on the new magic number { $Z(N) = 6$}, focusing on observables such as radii, binding energy, electromagnetic transition, and nucleon separation energies. We perform the {\it ab initio} no-core shell model calculations for the occupation numbers of {the lowest} single particle states in {the ground states of} {$Z(N)=6$ and $Z(N)=8$ isotopes (isotones)}. Our calculations do not support {$Z(N)=6$} as a magic number over a span of atomic numbers. However, $^{14}$C and $^{14}$O exhibit the characteristics of double-magic nuclei.

Dynamic response mechanisms of thin UHMWPE under high-speed impact

This study systematically explores the dynamic response mechanisms and energy dissipation mechanisms of ultra-high-molecular-weight polyethylene (UHMWPE) fiber laminated plates with thicknesses of 1.1 mm, 2.8 mm, and 5.4 mm under high-speed steel ball impacts through experimental, theoretical analysis, and dimensional analysis. By analyzing the damage mechanisms from experimental results, the main modes of energy absorption were identified, and a relatively accurate predictive model for ballistic limit speed was established. The results show that under high-speed steel ball impacts, the primary failure modes of UHMWPE fiber laminated plates are localized permanent bulging plastic deformation and perforation failure caused by compressive shear. The ballistic limit speeds for UHMWPE with thicknesses of 1.1 mm, 2.8 mm, and 5.4 mm are respectively 233.5 m/s, 415.7 m/s, and 602.9 m/s. The theoretical calculations of the energy model align well with the experimental results, indicating that as the speed increases, the proportion of tensile energy absorption gradually decreases, consistent with the observed phenomena. Near the ballistic limit, there are significant turning points in the level of energy absorption and the height of the rear bulge. The ballistic limit increases linearly with target thickness, and the unit area density energy absorption also increases continuously. Finally, this study established a dimensionless ballistic limit model considering the mechanical properties of fibers and the matrix, which through regression analysis, can accurately describe the ballistic limits of various strengths and types of fiber laminated plates, suitable for predicting the ballistic performance of various composite materials.

Radiation model and thermal characteristics of OLED glass substrate using electric heating tube

Glass substrate (GS) heating is a fundamental but significant technology for organic light emitting diode (OLED), which is critical to OLED displaying quality and efficiency. A rapid and reliable theoretical model is intensely demanded to guide practical system design, simulation analysis and experimental research for GS heating, but present radiative models are improper or inconvenient. Therefore, this paper establishes a new and direct calculation model with the addition of correctional coefficient 0.5 to blackbody radiation power of electric heating tube (EHT) and the proposal of comprehensive angle coefficient X, which can solve single and multi-source radiation problems theoretically. The simulation and experiment are both conducted for comparison analysis. The temperature errors of theory and simulation for multi EHTs are all within 1 % when compared with experimental results, which well validates the reliability and accuracy of theoretical and simulation models. Large EHT radius r, small distance L between EHT and GS, and suitable EHT number n are suggested, which benefits to the improvement of radiation heating and temperature uniformity of GS. It is hoped that this study can provide a useful tool on thermal radiation analysis and also a valuable promotion for practical OLED heating technology.

The Application of the Particle Element Method in Tubular Propellant Charge Structure: Lumped Element Method and Multiple-Element Method

Due to the orderly arrangement of tubular propellant, the permeability of combustion gases is improved, which is beneficial for enhancing the safety of the combustion system. However, current internal ballistic gas-solid flow calculation methods adopt a quasi-fluid assumption, which cannot accurately account for the characteristics of long tube shapes. Additionally, tubular propellants exhibit both overall movement and parameter distribution characteristics, necessitating the decoupling of gas and solid phases. These two deficiencies in previous studies have limited the effectiveness of gas-solid flow simulations for tubular propellant. This paper proposes a numerical calculation model suitable for tubular propellant charging based on the particle element method for internal ballistic two-phase flow. Firstly, considering the overall movement characteristics of tubular propellants, the concept of blank particle elements is introduced to represent pure gas phase regions. Then, based on computational requirements, the tubular propellants are divided to form the lumped element method and the multiple-element method. The moving boundary method is used to calculate the movement process of the propellant bed particle group and is compared with experimental results to verify the applicability of the two methods in tubular propellant beds. Analysis results show that the particle element method can effectively capture changes in the flow field inside the chamber and the position of tubular propellants. The lumped element method can quickly obtain the flow field distribution characteristics inside the chamber, while the multiple-element method can capture parameter distribution characteristics at different positions of the tubular propellants while ensuring overall movement.

Ebullition drives high methane emissions from a eutrophic coastal basin

The production of methane in coastal sediments and its release to the water column is intensified by anthropogenic eutrophication and bottom water hypoxia, and it is still uncertain whether methane emissions to the atmosphere will be enhanced. Here, we assess seasonal variations in methane dynamics in a eutrophic, seasonally euxinic coastal basin (Scharendijke, Lake Grevelingen). In-situ benthic chamber incubations reveal high rates of methane release from the sediment to the water column (74–163 mmol m−2 d−1) during monthly measurements between March and October 2021. Comparison of these in-situ total benthic methane fluxes and calculated diffusive fluxes point towards a major role for ebullition. In spring and fall, when the water column was oxic, microbial removal of dissolved methane occurred aerobically in the bottom water. In summer, in contrast, dissolved methane accumulated to concentrations of up to 67 μmol L−1 below the oxycline. Shifts in δ13C–CH4 and δD-CH4 towards higher values and the abundant presence of methane oxidizing bacteria point towards removal of methane around the oxycline, likely through both aerobic and anaerobic pathways, with the latter possibly linked to iron oxide reduction. Shifts in δ13C–CH4 and δD-CH4 to lower values above the oxycline indicate that bubble dissolution contributed to dissolved methane. Methane emissions to the atmosphere were observed in all seasons with the highest, in-situ measured diffusive fluxes (1.2 mmol m−2 d−1) upon the onset of water column mixing at the end of summer. Methane release events during the measurement of in-situ water-air fluxes and model calculations point towards a flux of methane to the atmosphere in the form of bubbles, which bypass the microbial methane filter. The model calculations suggest a potential year-round ebullitive methane flux between 30 and 120 mmol m−2 d−1. We conclude that methane emissions from eutrophic coastal systems may be much higher than previously thought because of ebullition.

Significant effect of salinity on zinc adsorption on tropical coastal and floodplain soils

AbstractRising sea levels due to climate change are causing increased salinisation of low‐lying coastal and floodplain soils, and the impact of this process on the bioavailability of plant nutrients needs to be understood as mitigation strategies are adapted. Zinc (Zn) is an element of particular importance due to its function as a micronutrient for plants including rice and other staple foods. In the current study, our aim was to investigate the effects of salinisation on zinc adsorption onto soils representing at‐risk coastal and floodplain environments, addressing in particular our knowledge gap concerning the roles that solution chemistry and soil composition play. To this end, we conducted batch adsorption experiments in the laboratory and ran geochemical models in saline solutions up to 0.7 mol L−1 ion strength incorporating both (i) a multi surface model (MSM) for surface reactions containing three phases, that is iron hydroxides, organic matter and phyllosilicate clays, and (ii) aqueous‐phase complexation to dissolved organic and inorganic ligands. Surface reactions were modelled using the diffuse double layer model, the NICA–Donnan model and an ion exchange model using the Gaines–Thomas convention. We combined the experimentally determined mass composition of surface phases with generic modelling parameters taken from the literature. We first show that increasing salinity enhances the formation of aqueous Zn‐chloride complexes in the presence of dissolved organic matter and bicarbonate, thereby decreasing the availability of free Zn2+ and supressing the partitioning of zinc to the adsorbed phase. We demonstrate using batch adsorption experiments with a calcareous hydraquent and a tropaquept, that salinity decreases zinc adsorption strongly in the pH range between 3 and 6. Satisfactory agreement between experiments and model calculations was achieved with root‐mean‐square errors ranging for different salinities between 2.88% and 2.92% for the hydraquent and between 4.59% and 2.74% for the tropaquept soil. Model predictions of adsorption were slightly inferior at low salinity for the hydraquent soil and at high salinity for the tropaquept soil, pointing possibly to an incomplete geochemical model or to a need to parametrise surface adsorption models at higher ionic strengths. Present surface models have been largely parametrised at lower ionic strength. We lastly apply the MSM to examine zinc adsorption in five endoaquepts soils, representing soil series from Bangladesh. We show that increasing salinity decreases zinc adsorption to the soil organic matter and the clay fractions. We conclude from our findings that increased soil salinity due to rising sea levels and climate change will have a significant impact on zinc cycling and possibly other micronutrients in areas where coastal soils and floodplain soils overlap, such as deltas and estuaries. In particular, we predict a decrease in zinc adsorption in acidic to neutral soils. The availability of zinc for biouptake through the roots of crop plants including rice will be significantly disturbed following salinisation, most likely affecting crop production. Our study demonstrates the potential that geochemical modelling combined with experimental data has to improve our capability to assess the effects of salinity due to rising seawater levels in vulnerable regions of the world.

Lubrication Characteristics of Dry-Gas Seals with Spiral Grooves

To obtain an optimal range of structural parameters for dry-gas seals with good performance, this study employed advanced sensing technology to monitor and analyze the internal flow characteristics of dry-gas seals in real time. Additionally, the validity of the calculation program was verified through experimentation. Using steady-state performance parameters as evaluation indices, a calculation model with lubrication characteristics was developed. The results indicate that when there are 12 grooves, the gas film pressure distribution is uniform and has a high value. At pressures greater than 2 MPa, the opening force, leakage, and gas film stiffness change significantly due to enhanced dynamic pressure effects with high-pressure differences, which reduces the local contact forces and frictional forces. At a constant speed, decreasing the gas film thickness increases the pressure difference while increasing both the opening force and film stiffness; however, at higher rotational speeds where the gas flow becomes non-uniform, the stability of the gas film is affected, leading to increased frictional forces. When there are between 10 and 16 grooves with depths ranging from 5.0 to 6.0 μm, dynamic pressure effects caused by pressure gradients become apparent, resulting in good dry-gas sealing performance being achieved. This research provides a theoretical reference for optimizing the design of dry-gas seals, as well as their steady-state seal performance.

A method to calculate the two-phase distribution in a microchannel heat exchanger

Maldistribution seriously impacts the heat transfer performance of the microchannel heat exchanger (MCHX). Fully understanding the two-phase distribution in the heat exchanger is important for advancing academic research and engineering applications. This study introduces a novel method for quantifying two-phase distribution in a microchannel heat exchanger. An experimental setup was developed to measure the local vapor mass fraction in the heat exchanger header. Capacitance signals were measured under inlet vapor mass fractions from 0 to 1, and inlet flow rates of 10, 15, and 25 g s−1 corresponding to a mass flux of 17.47, 26.2, and 43.66 kg m−2s−1, respectively. The local vapor mass fraction in the header was estimated using the capacitance measurements. The mass flow rate in the header, the microchannel tube, and the vapor mass fraction in the tube were calculated using the proposed model. The calculation model was validated against literature data, and the results were analyzed. The analysis reveals the characteristics of vapor mass fraction and mass flow rate distribution in the MCHX and further elaborates on the effects of phase separation, entrainment ratio, and pressure drop balance on the distribution. The proposed method can evaluate distribution in the header and tubes of microchannel heat exchangers, and it is also applicable to other types of two-phase flow devices.

Graph-Based Unsupervised Feature Selection for Interval-Valued Information System.

Feature selection has become one of the hot research topics in the era of big data. At the same time, as an extension of single-valued data, interval-valued data with its inherent uncertainty tend to be more applicable than single-valued data in some fields for characterizing inaccurate and ambiguous information, such as medical test results and qualified product indicators. However, there are relatively few studies on unsupervised attribute reduction for interval-valued information systems (IVISs), and it remains to be studied how to effectively control the dramatic increase of time cost in feature selection of large sample datasets. For these reasons, we propose a feature selection method for IVISs based on graph theory. Then, the model complexity could be greatly reduced after we utilize the properties of the matrix power series to optimize the calculation of the original model. Our approach can be divided into two steps. The first is feature ranking with the principles of relevance and nonredundancy, and the second is selecting top-ranked attributes when the number of features to keep is fixed as a priori. In this article, experiments are performed on 14 public datasets and the corresponding seven comparative algorithms. The results of the experiments verify that our algorithm is effective and efficient for feature selection in IVISs.

Synergetic Experimental and Theoretical Investigation of Molecular Structure – Optical Properties Relationships of Anthrazoline-Based Polymeric Chains

The photoluminescence and UV-Vis absorption spectra of copolyamides containing 1,9-anthrazoline with para- and meta-[(substituted carbonyl)amino]phenyl-1-ene moieties in a polymer backbone were studied by a combination of experimental and theoretical approaches. The investigation was accomplished through time-dependent density functional theory electronic structure calculations of small-molecule models mimicking a polymer chain. Theoretical absorption and luminescence spectra of ten atomistic models were compared with corresponding experimental data, and the optical properties of two new luminescent molecules with bromine auxochrome were predicted. An analysis of the optical properties demonstrate an identical effect of the type and position of a substituent on the spectra for para- and meta-[(substituted carbonyl)amino]phenyl-1-ene moieties. It was found that the absorption and luminescence spectra of theoretical para-models demonstrate red shifts relative to the corresponding meta- ones. The same phenomenon was observed in experimental spectra of low-molecular-mass compounds and corresponding copolyamides in solution and bulk. Unique optical properties allow anthrazoline-based polymer compounds to be used in numerous advanced optoelectronic applications with desired optical and electronic characteristics.

Predictive Model of variable laboratory findings calculation and monitoring during plasmapheresis procedures

Predictive Model of variable laboratory findings calculation and monitoring during plasmapheresis procedures

Web apps for profile fitting and power balance analysis at Wendelstein 7-X.

Two novel web apps for W7-X are introduced: Profile Cooker and Power House. They are designed to streamline the workflow of profile fitting and power balance analysis while offering a graphical user interface that works in any common browser. This allows us to compile a comprehensive database of experimental power balance results. All fitting functions available in Profile Cooker are presented and compared on the basis of example profiles. The power balance equation assumed in Power House is established and its individual terms are discussed. The main focus of the power balance analysis is on the turbulent transport coefficients. A model for quick calculation of neutral beam power deposition based on experimental profiles is presented. Neoclassical root transition poses an issue for power balance analysis due to the uncertainty of the radial electric field. A global, neoclassical simulation with the code EUTERPE is performed for a set of experimental profiles to gain an understanding of the neoclassical root transition.

Exploring the long-term variations and high concentration episodes of peroxyacetyl nitrate in Megacity Seoul

Over the past few years, peroxyacetyl nitrate (PAN) has drawn significant attention as a key indicator of photochemical pollution owing to its intimate relationship with ozone and associated health effects. This study presents measurements conducted at the Korea University campus in Seoul during the high-ozone seasons from 2018 to 2021. PAN concentration was measured using fast gas chromatography with luminol chemiluminescence detection (GC-LCD), alongside measurements of O3, volatile organic compounds (VOCs), NO, NO2, and meteorological variables, including boundary layer height (BLH).The mean concentrations of PAN and O3 over the years were 0.56 ppbv and 35 ppbv in 2018, 1.29 ppbv and 58 ppbv in 2019, 0.21 ppbv and 50 ppbv 2020, and 0.53 ppbv and 46 ppbv in 2021, respectively. The annual variation observed in Seoul is consistent with trends seen in major cities worldwide during the COVID19 pandemic, reflecting a substantial reduction in urban emissions. Indeed, the mean concentration of NOx and VOCs decreased significantly by more than 50 % and 25%, respectively, from 2019 to 2021.At temperatures above 30°C, PAN decomposition was accelerated, decoupling a consistent positive relationship between PAN and O3 in 2020 and 2021. The results of a 0-D photochemical model (F0AM) calculation demonstrated that PAN formation primarily stems from anthropogenic VOCs, particularly >C2 alkenes. Elevated PAN concentrations during nighttime were attributed to boundary layer expansion and upper-air entrainment. Instances where PAN concentrations surged to at least 3 ppbv or higher in 2019 were attributed to biomass burning impacted air, as evidenced by concurrent elevations in K+ and OC in PM2.5, and O3.This study underscores the complex interplay of factors influencing PAN and ozone enhancements under decreased precursor levels, with an emphasis on dynamic change in the boundary layer, and long-distance transport of non-fossil sources during agricultural burning seasons.

A Deep Learning Framework for IoT Lightweight Traffic Multi-classification: Smart-cities

Aim and Background: Increased traffic volume is a major challenge for effective network management in the wake of the proliferation of mobile computing and the Internet of Things (IoT). Earlier models surrender efficiency to achieve high-precision classification outcomes, which are no longer fitting for limited assets in edge network circumstances, making traffic classification a difficult task for network administrators everywhere. Given the nature of the problem, the current state of the art in traffic classification is characterized by extremely high computational complexity and large parameters. Methodology: To strike a clever balance between performance and size, we present a deep learning (DL)-based traffic classification model. We begin by decreasing the amount of model parameters and calculations by modifying the model's scale, width, and resolution. To further improve the capability of feature extraction at the traffic flow level, we secondly incorporate accurate geographical information on the attention mechanism. Thirdly, we get multiscale flow-level features by employing lightweight multiscale feature fusion. Results: The results of our experiments demonstrate that our model has high classification accuracy and efficient operation. Our study presents a traffic categorization model with an accuracy of over 99.82%, a parameter reduction of 0.26M, and a computation reduction of 5.26M. Conclusions: Therefore, this work offers a practical design used in a genuine IoT situation, where IoT traffic and tools' profiles are anticipated and classified while easing the data dispensation in the higher levels of an end-to-end communication strategy.

Melting temperature of iron under the Earth’s inner core condition from deep machine learning

Constraining the melting temperature of iron under Earth’s inner core conditions is crucial for understanding core dynamics and planetary evolution. Here, we develop a deep potential (DP) model for iron that explicitly incorporates electronic entropy contributions governing thermodynamics under Earth’s core conditions. Extensive benchmarking demonstrates the DP’s high fidelity across relevant iron phases and extreme pressure and temperature conditions. Through thermodynamic integration and direct solid–liquid coexistence simulations, the DP predicts melting temperatures for iron at the inner core boundary, consistent with previous ab initio results. This resolves the previous discrepancy of iron’s melting temperature at ICB between the DP model and ab initio calculation and suggests the crucial contribution of electronic entropy. Our work provides insights into machine learning melting behavior of iron under core conditions and provides the basis for future development of binary or ternary DP models for iron and other elements in the core.

Low-cost dealkalization of bauxite residue by gypsum coordinated with industrial iron salt: Mineralogical mechanisms and field practice

The sustained-release of alkalinity in bauxite residue hinders the soil formation and ecological restoration processes in disposal areas. Ferric salts (Fe3+), known for their rapid neutralization reaction process and straightforward operational simplicity, showed a synergistic advantage with gypsum (CaSO4) in the alkaline regulation of bauxite residue. Nevertheless, the mineralogical mechanisms of the reaction between Fe3+ and Ca2+ and alkaline minerals in bauxite residue remained unclear. The present study aimed to elucidate the geochemical stability mechanisms of sodalite and cancrinite, major alkaline minerals in bauxite residue, driven by Fe3+ and Ca2+ from a mineral structural perspective and the integrated restoration effect was demonstrated by the field experiment. Unreacted shrinking core model (USCM) calculations demonstrated that Fe3+ was able to enter the lattice structure of sodalite and cancrinite to replace Na+ and assisted Ca2+ in successfully replacing Na+ in cancrinite. Moreover, Fe3+ and Ca2+ facilitated the formation of insoluble coating layers on their surface. In the lattice structure of sodalite and cancrinite, the replacement reaction for Na+ was influenced by the competition between Fe3+ and Ca2+. The Ca2+ preferentially replaced Na+, while Fe3+ accumulated near the Si-O bonds, balancing the negative charges of the Si-O and Al-O tetrahedra structure and further inhibited alkaline mineral dissolution. The pH and EC of bauxite residue decreased from 10.52 to 7.60 and 712 μS/cm to 501 μS/cm, respectively, after a one-year field-scale amelioration by the integration of Fe3+ and Ca2+. These findings highlighted the synergistic roles of Fe3+ and Ca2+ in regulating the alkalinity of bauxite residue and provided a practical strategy for ecological restoration in disposal areas.

Determination of Chip Compression Ratio for the Orthogonal Cutting Process

The chip compression ratio is the most important characteristic of various machining processes with chip generation. This characteristic enables the determination of kinetic and other energy loads on the tool and the machined material. This provides an overall evaluation of the machining process and the possibility of its subsequent optimization. This paper presents the results of determining this cutting characteristic by experimental method, analytical calculation, and numerical modeling. For the analytical calculation of the chip compression ratio, an analytical cutting model developed based on the variational principle of the minimum potential energy was used. A finite element model of orthogonal cutting was used for the numerical simulation of the above process characteristic. Experimentally, the chip compression ratio was determined by the ratio of the chip thickness to the cutting depth (undeformed cutting thickness). The chip thickness was determined by direct measurement using chip slices obtained during the cutting process. The Johnson–Cook constitutive equation was used as the machined material model and the Coulomb model was used as the friction model. The generalized parameters’ determination of the constitutive equation was performed through a DOE (Design of Experiment) sensitivity analysis. The variation range of these parameters was chosen based on the analysis of the effect of individual parameters of the constitutive equation on the chip compression ratio value. The largest deviations between the experimental and analytically calculated values of the chip compression ratio did not exceed 21%. At the same time, the largest deviations of simulated values of the indicated cutting characteristic and its experimental values did not exceed 20%. When comparing the experimental values of the chip compression ratio with the corresponding calculated and simulated values, the deviations were within 22%.

An ionic liquid crystal functionalized nanocellulose lubricant additives

Cellulose, one of nature's most abundant, clean, and sustainable resources, has often shown unsatisfactory results when used as bio-lubricant additives. Herein, nanocellulose (NC) from amorphous waste natural poplar was extracted using deep eutectic solvent encapsulation treatment and chlorine bleaching process. Subsequently, 1-hexadecyl-3-methylimidazolium bromide was integrated onto NC using a one-step hydrothermal treatment (high-temperature and high-pressure environment) to obtain ionic liquid crystal (ILC) functionalized products (named as ILC-NC). After ball-milling process and solid phase separation step, ILC-NC exhibits excellent dispersion stability and lubrication properties in the liquid phase (including water and vegetable oil). Based on the polar and colloidal activity properties of ILC, it can form an ordered molecular layer on NC surface and form a lubricating film-like structure, making NC smoother and sliding well. Compared to ILC/NC aqueous dispersion, ILC-NC reduces the coefficient of friction and wear rate on steel disk surface by 68.75 % and 74.07 %, respectively. The minimum coefficient of friction was further reduced to 0.032 as dispersing ILC-NC in sunflower oil, showing a reduction of 0.134 (77.91 %) compared to pure sunflower oil. Finally, the lubrication theoretical model calculation reveals the lubrication state of ILC-NC on the steel disk surface and proposes the lubrication mechanism.